code: def get_n_parleys(opt):
      trainstats_suffix = ".trainstats"
      if opt.get("model_file") and PathManager.exists(
          opt["model_file"] + trainstats_suffix
      ):
          with PathManager.open(
              opt["model_file"] + trainstats_suffix
          ) as ts:
              obj = json.load(ts)
              parleys = obj.get("parleys", 0)
      else:
          parleys = 0
      return parleys
  
imports: from parlai.core.params import ParlaiParser, print_announcements
  from parlai.core.agents import create_agent
  from parlai.core.logs import TensorboardLogger
  from parlai.core.metrics import aggregate_named_reports, aggregate_unnamed_reports, Metric
  from parlai.core.opt import Opt
  from parlai.core.worlds import create_task
  from parlai.utils.misc import TimeLogger, nice_report
  from parlai.utils.world_logging import WorldLogger
  from parlai.core.script import ParlaiScript, register_script
  from parlai.utils.io import PathManager
  import parlai.utils.logging
  import json
  import os
  import random
  from parlai.utils.distributed import is_primary_worker, all_gather_list, is_distributed, get_rank
label_desc: Use image node_id 5 for calling a global function with example usage: get_n_parleys(opt) and returns: parleys